Momentum Based Strategies for Low and High Frequency Trading

Opinions tend to differ on what constitutes high frequency but by and large there is a consensus that the duration of asset holding period is very low, ranging from seconds to minutes. High frequency trading revolves around market microstructure and order book dynamics. HFT involves high volume of buying and selling to profit from time-sensitive opportunities that arise during trading hours. Firms depend upon low latency for order execution.

Low frequency trading includes intraday to inter-day buying and selling using the live tick data and technical analysis/ fundamental analysis. Low frequency trading uses daily or even less frequent data. LFT ignores market microstructure and bases strategies solely on trends and charts.

Momentum trading usually comes in the form of trends such as continuous upwards/downwards rallying of stock index, strong buying after a sharp decline etc. Traders focus on stocks that are moving significantly in one direction.

Momentum strategies in LFT

Momentum Indicators (Bearish and bullish)

The Momentum indicator compares where the current price is in relation to where the price was in the past. How far in the past the comparison is made is up to the technical analysis trader.

An example of the Momentum indicator is shown below in the chart of the E-mini Nasdaq 100 Future:

RSI-Neutral to breakout markets

When an ETF’s price is moving back and forth within a price band for an extended period of time, the RSI (14-day period) will likely fluctuate between 80 and 20. If the trading is really choppy, the RSI may even stay snug to a 50 reading.

When the price is moving within a range and the RSI is fluctuating between 20 and 80 traders are better off with a ranging strategy rather than a momentum strategy.

Figure below show this occurring for the United States Oil Fund (USO A). While there are opportunities to trade the see-saws in price, these are generally bypassed by momentum traders in favor of more dynamic moves.

Wait for the RSI to move out of this range before taking momentum trades. Ideally, an uptrend in price should result in the RSI reaching above 80 and also staying above 40. In a price downtrend, the RSI typically dips below 20 and generally stays below 60.

USO showed these tendencies back in 2012.

Cross sectional momentum (Long the winner, short the loser)

Cross-sectional momentum strategies are those which buy stocks with high returns over some past (formation) period and sell stocks with low returns over this same time period. Jegadeesh (1990) was the first author to document such an affect. In this article, Jegadeesh showed that stocks that have outperformed the cross-section over the previous months continue to have high returns over the next month. In contrast, stocks that had low returns relative to the cross-section continue their underperformance in the next month. A subsequent study by Jegadeesh and Titman (1993) confirmed these findings and showed the strategy performance can be improved by considering a set of formation versus holding periods.

Illustration of Cross Sectional Momentum

Cross Market Momentum

Time series momentum of Futures contract

Time series momentum is very simple and intuitive: past returns of a price series are positively correlated with future returns.

Time series momentum of a price series means that past returns are positively correlated with future returns. It follows that we can just calculate the correlation coefficient of the returns together with its p-value (which represents the probability for the null hypothesis of no correlation). One feature of computing the correlation coefficient is that we have to pick a specific time lag for the returns. Sometimes, the most positive correlations are between returns of different lags.

Example

1-day returns might show negative correlations, while the correlation between past 20-day return with the future 40-day return might be very positive. We should find the optimal pair of past and future periods that gives the highest positive correlation and use that as our look-back and holding period for our momentum strategy.

Opening gap strategy

The opposite momentum strategy will sometimes work on futures and currencies: buying when the instrument gaps up, and shorting when it gaps down

News driven momentum

Momentum is driven by the slow diffusion of news, surely we can benefit from the first few days, hours, or even seconds after a newsworthy event. This is the rationale behind traditional post–earnings announcement drift (PEAD) models, as well as other models based on various corporate or macroeconomic news.

Post earnings announcement drift

An unexplained downward movement of shares in companies following announcements that quarterly earnings have exceeded expectations.

The post-earnings-announcement drift is a long-standing anomaly that conflicts with market efficiency. This study documents that the post-earnings-announcement drift occurs mainly in highly illiquid stocks. A trading strategy that goes long high-earnings-surprise stocks and short low-earnings-surprise stocks provides a monthly value-weighted return of 0.04 percent in the most liquid stocks and 2.43 percent in the most illiquid stocks. The illiquid stocks have high trading costs and high market impact costs. By using a multitude of estimates, the study finds that transaction costs account for 70–100 percent of the paper profits from a long–short strategy designed to exploit the earnings momentum anomaly.

Momentum strategies have forms and can be based on a price or an indicator. To maximize opportunity apply momentum strategies in both up and down markets. During quiet and non-trending markets you’ll likely want to sit on the sidelines and await higher potential trades. When you’re trading momentum, the gains can be big, but so can the risks, as momentum can shift very quickly and severely. Control risk with a stop loss, and always trade with an exit plan in mind.

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